The Section on Neurophysiology studies the frontal cortex and related parts of the brain following five lines of recent research: the mechanisms of abstract response strategies and the selection of action based on past and future goals; the contribution of the frontal lobe in the calculation of time intervals; the role of the frontal cortex in the mapping of symbols to actions; the functional role of a particular part of the frontal lobe, called the ventral premotor cortex; and the role of the frontal cortex and basal ganglia in motor skill learning. These five lines of research are outlined briefly in the order listed above. Research line 1: In a paper published in 2005, Genovesio, Brasted, Mitz and Wise presented the first report of neural signals in prefrontal cortex that underlie the use of abstract response strategies. In the continuation of this research during the past year, we found that separate populations of neurons in prefrontal cortex encode previous and future goals, which are the starting materials and end products of the relevant neural computation. This separation between past and future goals is important to many daily life activities. If the distinction between already accomplished and not-yet-accomplished goals is degraded, a previous goal might be repeated inappropriately because it is wrongly represented as a future goal. Such perseverative behavior is a well-known result of frontal lobe dysfunction. Furthermore, if the frontal cortex cannot maintain a representation of a particular goal as already accomplished, this failure of the neural network could result in compulsive checking, which is one prominent symptom of obsessive-compulsive disorder. Conversely, if a future goal was wrongly construed as a past one, that goal will not be attempted and therefore it will not be achieved. This kind of mistake is common in Alzheimer?s dementia, which is often characterized failures of omission, a symptom that has also been reported in normal aging and in patients with schizophrenia. One possible explanation for these failures could be that, as shown in our research, the previous and future goals involve the same type of information. Given that fact, the only way to distinguish previous and future goals is to encode them in separate neuronal populations, and this is what we found and reported this year in a featured article in the Journal of Neuroscience (Genovesio, Brasted and Wise, 2006). Our work on abstract response strategies has also lead to a review article that provides original insights into the role of prefrontal cortex in higher brain functions (Genovesio and Wise, 2006). Research line 2: The second line of research deals with the computation of timing signals in the frontal cortex, in particular the computation of time intervals and durations of events. Misunderstanding structured event complexes and the timing of events is a common characteristic of Alzheimer?s dementia and is also one of the results of frontal lobe damage. During the past year, we have reported the existence of timing signals in the prefrontal cortex, research that was published in the Journal of Neurophysiology (Genovesio, Tsujimoto and Wise, 2006). We found that after the disappearance of a visual stimulus, many neurons showed phasic increases in activity that depended on the duration of that stimulus. This duration-dependent activity varied only weakly with reaction time and instead appeared to reflect a a very general aspect of elapsed time. One of our major ongoing projects is devoted to exploring the role of prefrontal cortex neurons in timing. Research line 3: The third line of research mentioned above involves the use of symbols to guide action, a process that we call symbolic mapping. Making decisions based on symbols is a fundamental feature of daily life, and diseases such as schizophrenia, attention deficit-hyperactivity disorder, obsessive-compulsive disorder, and others result, at least in part, from inappropriate selection and control of actions. In symbolic mapping, the choice of an action depends on the behavioral context provided by a symbol. This is the basis for learning the meaning of most words, linking meaning to speech, and for the wide variety of symbol-guided and signal-guided behavior that underlies most advanced human behavior. The previous years' work on this project has shown that symbolically guided action depends upon the proper functioning of specific parts of the frontal cortex, the hippocampal system and the basal ganglia. In the past year, our research along this line revealed that the one-trial learning of symbolic mappings depends on Hebbian mechanisms (Brasted, Bussey, Murray and Wise, 2005). We also found that the putamen, a part of the basal ganglia, retains the information needed for learning longer during the learning process than does the premotor cortex (Buch, Brasted and Wise, 2006). Research line 4: In addition, we have contributed to understanding the evolutionary history of various part of the frontal lobe. Wise (2006), in a special issue on "Integrative models of Broca?s area and the ventral premotor cortex" for the journal Cortex, described the evolutionary history of ventral premotor cortex and the role it plays in reaching and social signaling. In a book titled The Evolution of Nervous Systems, Wise (2006) elaborated on this contribution by synthesizing a wide range of evidence from comparative neuroanatomy, paleontology, comparative psychology, and traditional neuroscience which indicates that the ventral premotor cortex and its corticospinal projection reflects an adaptation to a hand-to-mouth, unimanual feeding technique. Wise argued that the ventral premotor cortex coordinates head, mouth, and limb movements during unimanual feeding. This idea developed the model explained in detail in the 2005 monograph by Shadmehr and Wise, published by MIT Press. That book presents a computational theory that includes the idea that ventral premotor cortex computes the difference between hand position and target location in a coordinate frame based on vision. Their theory showed furthermore that this computation could also support visually guided reaching and pointing, generally, as well as head orientation during social signaling. Research line 5: With co-authors who practice neuroimaging research, Wise reviewed the role of the basal ganglia in cognitive function, while with a different coauthor who specializes in motor psychophysics, he reviewed the literature on motor skill learning, both in The New Encyclopedia of Neuroscience (Aron, Wise and Poldrack, 2006; Wise and Willingham, 2006). These articles also build on the Shadmehr and Wise (2005) monograph. They explain that motor skill learning improves our ability to achieve goals by improving the spatial and temporal accuracy of our movements. The motor system learns how the body interacts with the world, and uses this knowledge to produce the forces needed to reach single or sequential targets. It does so, in part, by learning to correct both previous and ongoing errors. Neural networks involving parietal cortex, motor cortex and cerebellum correct errors made on previous movements, whereas overlapping networks involving cortex and basal ganglia correct ongoing movements. These and other networks acquire and produce practiced sequences of movements through both conscious and subconscious learning.